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An important relation in information extraction is the part-whole relation. Ontological studies mention several types of this relation. In this paper, we show that the traditional practice of initializing minimally-supervised algorithms with a single set that mixes seeds of different types fails to capture the wide variety of part-whole patterns and tuples. The results obtained with mixed seeds ultimately converge to one of the part-whole relation types. We also demonstrate that all the different types of part-whole relations can still be discovered, regardless of the type characterized by the initializing seeds. We performed our experiments with a state-ofthe-art information. | On Learning Subtypes of the Part-Whole Relation Do Not Mix your Seeds Ashwin Ittoo University of Groningen Groningen The Netherlands r.a.ittoo@rug.nl Gosse Bouma University of Groningen Groningen The Netherlands g.bouma@rug.nl Abstract An important relation in information extraction is the part-whole relation. Ontological studies mention several types of this relation. In this paper we show that the traditional practice of initializing minimally-supervised algorithms with a single set that mixes seeds of different types fails to capture the wide variety of part-whole patterns and tuples. The results obtained with mixed seeds ultimately converge to one of the part-whole relation types. We also demonstrate that all the different types of part-whole relations can still be discovered regardless of the type characterized by the initializing seeds. We performed our experiments with a state-of-the-art information extraction algorithm. 1 Introduction A fundamental semantic relation in many disciplines such as linguistics cognitive science and conceptual modelling is the part-whole relation which exists between parts and the wholes they compise Winston et al. 1987 Gerstl and Pribbenow 1995 . Different types of part-whole relations classified in various taxonomies are mentioned in literature Winston et al. 1987 Odell 1994 Gerstl and Pribbenow 1995 Keet and Artale 2008 . The taxonomy of Keet and Artale 2008 for instance distinguishes part-whole relations based on their transitivity and on the semantic classes of entities they sub-categorize. Part-whole relations are also crucial for many information extraction IE tasks Girju et al. 2006 . Annotated corpora and semantic dictionaries used in IE such as the ACE corpus1 and WordNet Fell-baum 1998 include examples of part-whole relations. Also previous relation extraction work 1http projects.ldc.upenn.edu ace such as Berland and Charniak 1999 and Girju et al. 2006 have specifically targeted the discovery of part-whole relations .
